templates: memory chatbot and vector rag notes (#8788)

* fix-note

* remove-oss-language-in-note
This commit is contained in:
Mendon Kissling 2025-06-30 16:38:43 -04:00 committed by GitHub
commit fd685382f4
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2 changed files with 232 additions and 217 deletions

View file

@ -7,7 +7,7 @@
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@ -15,7 +15,7 @@
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@ -44,19 +44,19 @@
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@ -100,7 +100,7 @@
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@ -109,18 +109,18 @@
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@ -405,7 +405,7 @@
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@ -426,7 +426,7 @@
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@ -728,9 +728,9 @@
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"description": "# Memory Chatbot\n\nA flexible chatbot implementation featuring advanced conversation memory capabilities. This serves as a foundational tool for building chat experiences with persistent context.\n\n## Core Components\n\n1. **Chat Input**\n - Accepts user messages\n - Configures conversation storage\n - Tracks session identity\n\n2. **Chat Memory**\n - Stores and retrieves up to 100 previous messages\n - Maintains conversation context\n - Tracks separate chat sessions\n - Preserves sender information and message order\n\n3. **Prompt**\n - Creates dynamic prompt templates\n - Integrates memory into conversation flow\n\n4. **OpenAI**\n - Processes user input with context\n - Accesses conversation history\n - Includes options for model configuration and API key setup\n\n5. **Chat Output**\n - Displays formatted responses\n - Maintains conversation flow\n - Syncs with memory storage\n\n## Memory Features\n\n- Stores message history\n- Plans conversation trajectory\n- Differentiates between chat sessions\n- Preserves sender and message metadata\n\n## Quick Start\n\n1. **Initialize** with a clear session ID\n2. **Enter** message in Chat Input\n3. **AI Processes** with context from memory\n4. **Response** appears in Chat Output\n5. Context remains available for follow-ups\n\nThis robust system demonstrates thorough memory integration with minimal complexity. 🧠💬\n",
"description": "# Memory Chatbot\n\nThis flow extends the basic prompting flow with a Message history component that stores up to 100 previous chat messages and uses them to provide context for the current conversation.\n\n## Prerequisites\n\n* [OpenAI API Key](https://platform.openai.com/)\n\n## Quickstart\n\n1. In the **Language Model** component, add your OpenAI API Key.\n\n2. Open the **Playground**. Tell the chat your name.\n\n3. Start a new chat session in the Playground, and ask, `what is my name`. The Prompt component will still remember your name, because it's connected to the Message History component.\n\n",
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@ -738,15 +738,15 @@
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"description": "## Get Your OpenAI API Key\n\n**Steps**:\n\n1. **Visit** [OpenAI's API Key Page](https://platform.openai.com/api-keys).\n\n2. **Log In/Sign Up**:\n - Log in or create a new OpenAI account.\n\n3. **Generate API Key**:\n - Click \"Create New Secret Key\" to obtain your key.\n\n4. **Store Your Key Securely**:\n - Note it down as it will only display once.\n\n5. **Enter API Key**:\n - Input your key in the OpenAI API Key field within the component setup.\n\nKeep your key safe and manage it responsibly!",
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@ -1560,13 +1528,14 @@
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View file

@ -7,7 +7,7 @@
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"data": {
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"name": "message",
"output_types": [
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"sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-g8ha3œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
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@ -157,7 +157,7 @@
},
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@ -178,7 +178,7 @@
"data": {
"sourceHandle": {
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"id": "SplitText-6H5cD",
"name": "dataframe",
"output_types": [
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@ -186,7 +186,7 @@
},
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"id": "AstraDB-H2sZ0",
"id": "AstraDB-W6NB4",
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"DataFrame"
@ -194,12 +194,12 @@
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}
},
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"sourceHandle": "{œdataTypeœ: œSplitTextœ, œidœ: œSplitText-iHZQkœ, œnameœ: œdataframeœ, œoutput_typesœ: [œDataFrameœ]}",
"target": "AstraDB-H2sZ0",
"targetHandle": "{œfieldNameœ: œingest_dataœ, œidœ: œAstraDB-H2sZ0œ, œinputTypesœ: [œDataœ, œDataFrameœ], œtypeœ: œotherœ}"
"source": "SplitText-6H5cD",
"sourceHandle": "{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-6H5cDœ,œnameœ:œdataframeœ,œoutput_typesœ:[œDataFrameœ]}",
"target": "AstraDB-W6NB4",
"targetHandle": "{œfieldNameœ:œingest_dataœ,œidœ:œAstraDB-W6NB4œ,œinputTypesœ:[œDataœ,œDataFrameœ],œtypeœ:œotherœ}"
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@ -207,7 +207,7 @@
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"id": "File-J8GVA",
"id": "File-vusZ2",
"name": "message",
"output_types": [
"Message"
@ -215,7 +215,7 @@
},
"targetHandle": {
"fieldName": "data_inputs",
"id": "SplitText-iHZQk",
"id": "SplitText-6H5cD",
"inputTypes": [
"Data",
"DataFrame",
@ -224,19 +224,20 @@
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}
},
"id": "xy-edge__File-J8GVA{œdataTypeœ:œFileœ,œidœ:œFile-J8GVAœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-SplitText-iHZQk{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-iHZQkœ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œotherœ}",
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"sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-J8GVAœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
"target": "SplitText-iHZQk",
"targetHandle": "{œfieldNameœ: œdata_inputsœ, œidœ: œSplitText-iHZQkœ, œinputTypesœ: [œDataœ, œDataFrameœ, œMessageœ], œtypeœ: œotherœ}"
"source": "File-vusZ2",
"sourceHandle": "{œdataTypeœ:œFileœ,œidœ:œFile-vusZ2œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}",
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"targetHandle": "{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-6H5cDœ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œotherœ}"
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"className": "",
"data": {
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"id": "Prompt-HCuAj",
"id": "Prompt-V3tlJ",
"name": "prompt",
"output_types": [
"Message"
@ -244,25 +245,27 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "LanguageModelComponent-cmjdt",
"id": "LanguageModelComponent-1uhUK",
"inputTypes": [
"Message"
],
"type": "str"
}
},
"id": "xy-edge__Prompt-HCuAj{œdataTypeœ:œPromptœ,œidœ:œPrompt-HCuAjœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-LanguageModelComponent-cmjdt{œfieldNameœ:œinput_valueœ,œidœ:œLanguageModelComponent-cmjdtœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-HCuAj",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-HCuAjœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "LanguageModelComponent-cmjdt",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œLanguageModelComponent-cmjdtœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-Prompt-V3tlJ{œdataTypeœ:œPromptœ,œidœ:œPrompt-V3tlJœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-LanguageModelComponent-1uhUK{œfieldNameœ:œinput_valueœ,œidœ:œLanguageModelComponent-1uhUKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"selected": false,
"source": "Prompt-V3tlJ",
"sourceHandle": "{œdataTypeœ:œPromptœ,œidœ:œPrompt-V3tlJœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}",
"target": "LanguageModelComponent-1uhUK",
"targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œLanguageModelComponent-1uhUKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"
},
{
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"className": "",
"data": {
"sourceHandle": {
"dataType": "LanguageModelComponent",
"id": "LanguageModelComponent-cmjdt",
"id": "LanguageModelComponent-1uhUK",
"name": "text_output",
"output_types": [
"Message"
@ -270,7 +273,7 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "ChatOutput-mfQ3f",
"id": "ChatOutput-ZaYDW",
"inputTypes": [
"Data",
"DataFrame",
@ -279,11 +282,12 @@
"type": "str"
}
},
"id": "xy-edge__LanguageModelComponent-cmjdt{œdataTypeœ:œLanguageModelComponentœ,œidœ:œLanguageModelComponent-cmjdtœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-mfQ3f{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-mfQ3fœ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œstrœ}",
"source": "LanguageModelComponent-cmjdt",
"sourceHandle": "{œdataTypeœ: œLanguageModelComponentœ, œidœ: œLanguageModelComponent-cmjdtœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-mfQ3f",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-mfQ3fœ, œinputTypesœ: [œDataœ, œDataFrameœ, œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-LanguageModelComponent-1uhUK{œdataTypeœ:œLanguageModelComponentœ,œidœ:œLanguageModelComponent-1uhUKœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-ZaYDW{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-ZaYDWœ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œstrœ}",
"selected": false,
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"sourceHandle": "{œdataTypeœ:œLanguageModelComponentœ,œidœ:œLanguageModelComponent-1uhUKœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}",
"target": "ChatOutput-ZaYDW",
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}
],
"nodes": [
@ -291,7 +295,7 @@
"data": {
"description": "Get chat inputs from the Playground.",
"display_name": "Chat Input",
"id": "ChatInput-g8ha3",
"id": "ChatInput-et7o5",
"node": {
"base_classes": [
"Message"
@ -558,7 +562,7 @@
},
"dragging": false,
"height": 234,
"id": "ChatInput-g8ha3",
"id": "ChatInput-et7o5",
"measured": {
"height": 234,
"width": 320
@ -579,7 +583,7 @@
"data": {
"description": "Create a prompt template with dynamic variables.",
"display_name": "Prompt",
"id": "Prompt-HCuAj",
"id": "Prompt-V3tlJ",
"node": {
"base_classes": [
"Message"
@ -740,7 +744,7 @@
},
"dragging": false,
"height": 433,
"id": "Prompt-HCuAj",
"id": "Prompt-V3tlJ",
"measured": {
"height": 433,
"width": 320
@ -761,7 +765,7 @@
"data": {
"description": "Split text into chunks based on specified criteria.",
"display_name": "Split Text",
"id": "SplitText-iHZQk",
"id": "SplitText-6H5cD",
"node": {
"base_classes": [
"Data"
@ -947,7 +951,7 @@
},
"dragging": false,
"height": 475,
"id": "SplitText-iHZQk",
"id": "SplitText-6H5cD",
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"width": 320
@ -966,7 +970,7 @@
},
{
"data": {
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"id": "note-rR7dl",
"node": {
"description": "## 🐕 2. Retriever Flow\n\nThis flow answers your questions with contextual data retrieved from your vector database.\n\nOpen the **Playground** and ask, \n\n```\nWhat is this document about?\n```\n",
"display_name": "",
@ -979,7 +983,7 @@
},
"dragging": false,
"height": 324,
"id": "note-B9a7p",
"id": "note-rR7dl",
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"width": 324
@ -1003,7 +1007,7 @@
},
{
"data": {
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"id": "note-zTYux",
"node": {
"description": "## 📖 README\n\nLoad your data into a vector database with the 📚 **Load Data** flow, and then use your data as chat context with the 🐕 **Retriever** flow.\n\n**🚨 Add your OpenAI API key as a global variable to easily add it to all of the OpenAI components in this flow.** \n\n**Quick start**\n1. Run the 📚 **Load Data** flow.\n2. Run the 🐕 **Retriever** flow.\n\n**Next steps** \n\n- Experiment by changing the prompt and the loaded data to see how the bot's responses change. \n\nFor more info, see the [Langflow docs](https://docs.langflow.org/starter-projects-vector-store-rag).",
"display_name": "Read Me",
@ -1015,11 +1019,11 @@
"type": "note"
},
"dragging": false,
"height": 324,
"id": "note-zlGxX",
"height": 556,
"id": "note-zTYux",
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"height": 556,
"width": 389
},
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"x": 191.12162720143235,
@ -1036,13 +1040,13 @@
"width": 324
},
"type": "noteNode",
"width": 324
"width": 389
},
{
"data": {
"description": "Display a chat message in the Playground.",
"display_name": "Chat Output",
"id": "ChatOutput-mfQ3f",
"id": "ChatOutput-ZaYDW",
"node": {
"base_classes": [
"Message"
@ -1325,7 +1329,7 @@
},
"dragging": false,
"height": 234,
"id": "ChatOutput-mfQ3f",
"id": "ChatOutput-ZaYDW",
"measured": {
"height": 234,
"width": 320
@ -1344,7 +1348,7 @@
},
{
"data": {
"id": "OpenAIEmbeddings-LqNei",
"id": "OpenAIEmbeddings-v0rcw",
"node": {
"base_classes": [
"Embeddings"
@ -1821,7 +1825,7 @@
},
"dragging": false,
"height": 320,
"id": "OpenAIEmbeddings-LqNei",
"id": "OpenAIEmbeddings-v0rcw",
"measured": {
"height": 320,
"width": 320
@ -1840,9 +1844,9 @@
},
{
"data": {
"id": "note-qlZFl",
"id": "note-i07aq",
"node": {
"description": "## 📚 1. Load Data Flow\n\nRun this first! Load data from a local file and embed it into the vector database.\n\nSelect a Database and a Collection, or create new ones. \n\nClick ▶️ **Run component** on the **Astra DB** component to load your data.\n\n* If you're using OSS Langflow, add your Astra DB Application Token to the Astra DB component.\n\n#### Next steps:\n Experiment by changing the prompt and the contextual data to see how the retrieval flow's responses change.",
"description": "## 📚 1. Load Data Flow\n\nRun this first! Load data from a local file and embed it into the vector database.\n\nSelect a Database and a Collection, or create new ones. \n\nClick **Run component** on the **Astra DB** component to load your data.\n\n\n### Next steps:\n Experiment by changing the prompt and the contextual data to see how the retrieval flow's responses change.",
"display_name": "",
"documentation": "",
"template": {
@ -1852,15 +1856,15 @@
"type": "note"
},
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"height": 324,
"id": "note-qlZFl",
"height": 460,
"id": "note-i07aq",
"measured": {
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},
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"y": 1552.171191793604
"x": 913.9906853654297,
"y": 1523.8879126168624
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"positionAbsolute": {
"x": 955.3277857006676,
@ -1873,11 +1877,11 @@
"width": 324
},
"type": "noteNode",
"width": 324
"width": 340
},
{
"data": {
"id": "OpenAIEmbeddings-EjaQd",
"id": "OpenAIEmbeddings-oFtHy",
"node": {
"base_classes": [
"Embeddings"
@ -2354,7 +2358,7 @@
},
"dragging": false,
"height": 320,
"id": "OpenAIEmbeddings-EjaQd",
"id": "OpenAIEmbeddings-oFtHy",
"measured": {
"height": 320,
"width": 320
@ -2373,7 +2377,7 @@
},
{
"data": {
"id": "note-p3NKF",
"id": "note-YhXtV",
"node": {
"description": "### 💡 Add your OpenAI API key here 👇",
"display_name": "",
@ -2386,7 +2390,7 @@
},
"dragging": false,
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"id": "note-p3NKF",
"id": "note-YhXtV",
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@ -2405,7 +2409,7 @@
},
{
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"id": "note-msH3w",
"id": "note-AdydJ",
"node": {
"description": "### 💡 Add your OpenAI API key here 👇",
"display_name": "",
@ -2418,7 +2422,7 @@
},
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},
{
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"id": "note-5lklz",
"id": "note-aBKhj",
"node": {
"description": "### 💡 Add your OpenAI API key here 👇",
"display_name": "",
@ -2450,7 +2454,7 @@
},
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"id": "note-5lklz",
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@ -2469,7 +2473,7 @@
},
{
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"id": "parser-ehrBO",
"id": "parser-WUXPk",
"node": {
"base_classes": [
"Message"
@ -2631,9 +2635,9 @@
"type": "parser"
},
"dragging": false,
"id": "parser-ehrBO",
"id": "parser-WUXPk",
"measured": {
"height": 360,
"height": 361,
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},
"position": {
@ -2645,7 +2649,7 @@
},
{
"data": {
"id": "AstraDB-qCu1f",
"id": "AstraDB-JsRrT",
"node": {
"base_classes": [
"Data",
@ -2697,6 +2701,8 @@
"group_outputs": false,
"method": "search_documents",
"name": "search_results",
"options": null,
"required_inputs": null,
"selected": "Data",
"tool_mode": true,
"types": [
@ -2711,6 +2717,8 @@
"group_outputs": false,
"method": "as_dataframe",
"name": "dataframe",
"options": null,
"required_inputs": null,
"selected": "DataFrame",
"tool_mode": true,
"types": [
@ -2726,6 +2734,8 @@
"hidden": true,
"method": "as_vector_store",
"name": "vectorstoreconnection",
"options": null,
"required_inputs": null,
"selected": "VectorStore",
"tool_mode": true,
"types": [
@ -2765,7 +2775,7 @@
"info": "The API Endpoint for the Astra DB instance. Supercedes database selection.",
"list": false,
"list_add_label": "Add More",
"load_from_db": true,
"load_from_db": false,
"name": "api_endpoint",
"placeholder": "",
"required": false,
@ -2774,7 +2784,7 @@
"tool_mode": false,
"trace_as_metadata": true,
"type": "str",
"value": "ASTRA_DB_API_ENDPOINT"
"value": ""
},
"astradb_vectorstore_kwargs": {
"_input_type": "NestedDictInput",
@ -3061,8 +3071,21 @@
"dynamic": false,
"info": "The Database name for the Astra DB instance.",
"name": "database_name",
"options": [],
"options_metadata": [],
"options": [
"us-east-2"
],
"options_metadata": [
{
"api_endpoint": "https://5b8bb22c-4a38-4f0a-865c-a18ed7590bd1-us-east-2.apps.astra.datastax.com",
"collections": 5,
"keyspaces": [
"default_keyspace",
"samples_dataflow"
],
"org_id": "260f986d-e65c-4f05-94a3-7cebfcb867a3",
"status": null
}
],
"placeholder": "",
"real_time_refresh": true,
"refresh_button": true,
@ -3393,9 +3416,9 @@
"type": "AstraDB"
},
"dragging": false,
"id": "AstraDB-qCu1f",
"id": "AstraDB-JsRrT",
"measured": {
"height": 501,
"height": 502,
"width": 320
},
"position": {
@ -3407,7 +3430,7 @@
},
{
"data": {
"id": "AstraDB-H2sZ0",
"id": "AstraDB-W6NB4",
"node": {
"base_classes": [
"Data",
@ -3459,6 +3482,8 @@
"group_outputs": false,
"method": "search_documents",
"name": "search_results",
"options": null,
"required_inputs": null,
"selected": "Data",
"tool_mode": true,
"types": [
@ -3473,6 +3498,8 @@
"group_outputs": false,
"method": "as_dataframe",
"name": "dataframe",
"options": null,
"required_inputs": null,
"selected": "DataFrame",
"tool_mode": true,
"types": [
@ -3488,6 +3515,8 @@
"hidden": true,
"method": "as_vector_store",
"name": "vectorstoreconnection",
"options": null,
"required_inputs": null,
"selected": "VectorStore",
"tool_mode": true,
"types": [
@ -3526,7 +3555,7 @@
"info": "The API Endpoint for the Astra DB instance. Supercedes database selection.",
"list": false,
"list_add_label": "Add More",
"load_from_db": true,
"load_from_db": false,
"name": "api_endpoint",
"placeholder": "",
"required": false,
@ -3535,7 +3564,7 @@
"tool_mode": false,
"trace_as_metadata": true,
"type": "str",
"value": "ASTRA_DB_API_ENDPOINT"
"value": ""
},
"astradb_vectorstore_kwargs": {
"_input_type": "NestedDictInput",
@ -3822,8 +3851,21 @@
"dynamic": false,
"info": "The Database name for the Astra DB instance.",
"name": "database_name",
"options": [],
"options_metadata": [],
"options": [
"us-east-2"
],
"options_metadata": [
{
"api_endpoint": "https://5b8bb22c-4a38-4f0a-865c-a18ed7590bd1-us-east-2.apps.astra.datastax.com",
"collections": 5,
"keyspaces": [
"default_keyspace",
"samples_dataflow"
],
"org_id": "260f986d-e65c-4f05-94a3-7cebfcb867a3",
"status": null
}
],
"placeholder": "",
"real_time_refresh": true,
"refresh_button": true,
@ -4149,13 +4191,14 @@
},
"tool_mode": false
},
"selected_output": "search_results",
"showNode": true,
"type": "AstraDB"
},
"dragging": false,
"id": "AstraDB-H2sZ0",
"id": "AstraDB-W6NB4",
"measured": {
"height": 501,
"height": 502,
"width": 320
},
"position": {
@ -4167,7 +4210,7 @@
},
{
"data": {
"id": "File-J8GVA",
"id": "File-vusZ2",
"node": {
"base_classes": [
"Message"
@ -4204,6 +4247,8 @@
"group_outputs": false,
"method": "load_files_message",
"name": "message",
"options": null,
"required_inputs": null,
"selected": "Message",
"tool_mode": true,
"types": [
@ -4433,9 +4478,9 @@
"type": "File"
},
"dragging": false,
"id": "File-J8GVA",
"id": "File-vusZ2",
"measured": {
"height": 229,
"height": 230,
"width": 320
},
"position": {
@ -4447,7 +4492,7 @@
},
{
"data": {
"id": "LanguageModelComponent-cmjdt",
"id": "LanguageModelComponent-1uhUK",
"node": {
"base_classes": [
"LanguageModel",
@ -4721,13 +4766,14 @@
},
"tool_mode": false
},
"selected_output": "text_output",
"showNode": true,
"type": "LanguageModelComponent"
},
"dragging": false,
"id": "LanguageModelComponent-cmjdt",
"id": "LanguageModelComponent-1uhUK",
"measured": {
"height": 450,
"height": 451,
"width": 320
},
"position": {
@ -4739,14 +4785,14 @@
}
],
"viewport": {
"x": -15.798686238525761,
"y": -165.1033705691603,
"zoom": 0.4569209426006492
"x": -22.84629031494228,
"y": -151.44728538879235,
"zoom": 0.45963552948592706
}
},
"description": "Load your data for chat context with Retrieval Augmented Generation.",
"endpoint_name": null,
"id": "769ebe18-11b2-4cb3-96a3-eef00d86578e",
"id": "b65cafc6-9f8e-4137-ad2b-4c663822f512",
"is_component": false,
"last_tested_version": "1.4.3",
"name": "Vector Store RAG",